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Clifford H. Spiegelman
Researcher at Texas A&M University
Publications - 96
Citations - 3563
Clifford H. Spiegelman is an academic researcher from Texas A&M University. The author has contributed to research in topics: Calibration (statistics) & Regression analysis. The author has an hindex of 26, co-authored 95 publications receiving 3374 citations. Previous affiliations of Clifford H. Spiegelman include National Agricultural Statistics Service & University of Texas Medical Branch.
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Journal ArticleDOI
Multi-site assessment of the precision and reproducibility of multiple reaction monitoring–based measurements of proteins in plasma
Terri A. Addona,Susan E. Abbatiello,Birgit Schilling,Steven J. Skates,D. R. Mani,David M. Bunk,Clifford H. Spiegelman,Lisa J. Zimmerman,Amy-Joan L. Ham,Hasmik Keshishian,Steven C. Hall,Simon Allen,Ronald K. Blackman,Christoph H. Borchers,Charles Buck,Helene L. Cardasis,Michael P. Cusack,Nathan G. Dodder,Bradford W. Gibson,Jason M. Held,Tara Hiltke,Angela M. Jackson,Eric B. Johansen,Christopher R. Kinsinger,Jing Li,Mehdi Mesri,Thomas A. Neubert,Richard K. Niles,Trenton C. Pulsipher,David F. Ransohoff,Henry Rodriguez,Paul A. Rudnick,Derek Smith,David L. Tabb,Tony J. Tegeler,Asokan Mulayath Variyath,Lorenzo Vega-Montoto,Asa Wahlander,Sofia Waldemarson,Mu Wang,Jeffrey R. Whiteaker,Lei Zhao,N. Leigh Anderson,Susan J. Fisher,Daniel C. Liebler,Amanda G. Paulovich,Fred E. Regnier,Paul Tempst,Steven A. Carr +48 more
TL;DR: A multilaboratory study to assess reproducibility, recovery, linear dynamic range and limits of detection and quantification of multiplexed, MRM-based assays, conducted by NCI-CPTAC demonstrates that these assays can be highly reproducible within and across laboratories and instrument platforms.
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Testing the Goodness of Fit of a Linear Model via Nonparametric Regression Techniques
TL;DR: In this article, the use of nonparametric regression methodology to test the adequacy of a parametric linear model is investigated, and the results demonstrate that such tests are consistent against all fixed smooth alternatives to linearity but are incapable of detecting local alternatives converging to a linear model at the parametric rate n −1/2.
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Theoretical Justification of Wavelength Selection in PLS Calibration : Development of a New Algorithm
Clifford H. Spiegelman,Michael J. McShane,M.J. Goetz,Massoud Motamedi,Qin Li Yue,Gerard L. Coté +5 more
TL;DR: It was concluded that careful design of a selection algorithm should include consideration of spectral noise distributions in the input data to increase the likelihood of successful and appropriate selection for data with noise distributions resulting in large outliers.
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On errors-in-variables for binary regression models
TL;DR: In this paper, the authors consider binary regression models when some of the predictors are measured with error and show that if the measurement error is large, the usual estimate of the probability of the event in question can be substantially in error, especially for high risk groups.
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Population and temperature effects on Lucilia sericata (Diptera: Calliphoridae) body size and minimum development time.
TL;DR: This study determined the minimum time of development and pupal sizes of three populations of Lucilia sericata Meigen at two temperatures (20°C and 33.5°C).